Evidence map›Paper›PMID 39190427›Full record

ReviewJournal of medical Internet research2024

Deceptively Simple yet Profoundly Impactful: Text Messaging Interventions to Support Health.

Brian Suffoletto

Abstract readReview
In one paragraph

Review in Journal of medical Internet research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
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  5. Observational
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  13. Observational
  14. Applying Innovative Methods to Develop Health Education Text Messages in Cancer Survivorship.Journal of cancer education : the official journal of the American Association for Cancer Education · 2026
    Article
  15. Article
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  18. Development of a Health Text Message System to Support Stroke Prevention: A Component of the Love Your Brain Digital Platform.Health expectations : an international journal of public participation in health care and health policy · 2025
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Brian SuffolettoDepartment of Emergency Medicine, Stanford University, Palo Alto, CA, United States.ORCID 0000-0002-9628-5260

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper examines the use of text message (SMS) interventions for health-related behavioral support. It first outlines the historical progress in SMS intervention research publications and the variety of funds from US government agencies. A narrative review follows, highlighting the effectiveness of SMS interventions in key health areas, such as physical activity, diet and weight loss, mental health, and substance use, based on published meta-analyses. It then outlines advantages of text messaging compared to other digital modalities, including the real-time capability to collect information and deliver microdoses of intervention support. Crucial design elements are proposed to optimize effectiveness and longitudinal engagement across communication strategies, psychological foundations, and behavior change tactics. We then discuss advanced functionalities, such as the potential for generative artificial intelligence to improve user interaction. Finally, major challenges to implementation are highlighted, including the absence of a dedicated commercial platform, privacy and security concerns with SMS technology, difficulties integrating SMS interventions with medical informatics systems, and concerns about user engagement. Proposed solutions aim to facilitate the broader application and effectiveness of SMS interventions. Our hope is that these insights can assist researchers and practitioners in using SMS interventions to improve health outcomes and reducing disparities.

Indexed as

Text MessagingHealth BehaviorHumansbehaviorbehaviorsbehaviourbehaviourschatbotchatbotsdevelopmentdieteffectivenessimpactinterventioninterventionslarge language modellarge language modelsLLMmental healthmeta-analysismobile phonenarrative reviewphysical activityreviewSMSSMS interventionsubstance usetext messagingweight loss

Identifiers

PMID39190427
PMCPMC11387917

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.